• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.457-465
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• 2004

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1647-1651
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• 2009

The uncertainty or imprecision associated with vague parameters and weighting sets, reduces the ability to decide what alternative is better for a particular location. To efficiently reduce the effect of imprecision frequently arising in available information, fuzzy theory has been used to improve consideration of imprecision in a Multi-Criteria Decision Analysis (MCDA) problem. Fuzzy logic offers a way to represent and handle imprecision present in continuous real world applications. A GIS implementing fuzzy set theory, (referred to in this paper as the "Spatial Fuzzy Approach") enables decision makers to express imprecise concepts associated with geographic data and provides decision makers the ability to have even more definition and discrimination in terms of the best alternatives for a particular spatial location. This study is focused on addressing questions pertaining to the methodology of floodplain analysis using GIS and Spatial Fuzzy MCDA to evaluate flood damage reduction alternatives. The issues will be examined in a case study of the Suyoung River Basin in Pusan, Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.11-23
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• 1998

This paper presents a more efficient evaluation of alternatives by use of multi-criteria decision making methodlogy under fuzzy intersectional dependence relations. The performance evaluation of most systems such as weapons, enterprise systems etc. are multiple criteria decision making problems. The descriptions and judgements on these systems are usually linguistic and fuzzy. The traditional methods of Analytic Hierarchy Process(AHP) are mainly used in crisp(non-fuzzy) decision applications with a very unbalanced scale of judgements and rank reversal. To overcome these problems, we will propose a new, general decision making method for evaluation models using fuzzy AHP(FAHP) under fuzzy intersectional dependence relations. The T.M.S alternatives A, B and C will be evaluted by the Fuzzy Analytic Hierachy Process (FAHP) based on entropy weight in this study. We will use symmetric triangular fuzzy numbers to indicate the relative strength of the elements in the hierachy and degree of intersection between criteria. These problems are evaluated by five criteria : tactical criteria, technology criteria, maintenance criteria, economy criteria, advacement criteria.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.635-643
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• 1997

The purpose of this paper is to propose an interactive method, using fuzzy Choquet's integral, which is designed to find out the mostly preferred solutions for deterministic MADM problems with many attributes and alternatives. The basic idea of the paper is essentially the same as that of the one we have published before[1]; subgrouping of attributes and eliminating of inefficient solutions. But the difference between these two methods lies in the fact that the present method evaluates and eliminates alternatives using fuzzy Choquet's integral on the basis of decision-maker's judgements about the relative importance of subgroups of attributes, rather than using mathematical programming on the basis of pair-wise comparisons of alternatives. If such information is obtainable from the decision-maker, the method can be proved to be much easier to understand and more efficient to compute.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.57-73
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• 2006

This paper describes a methodology for automating the material handling equipment (MHE) evaluation and selection processes by combining knowledge-based rules and fuzzy multi-criteria decision making approach. The methodology is proposed to solve the MHE selection problems under fuzzy environment. At the primary stage, the most appropriate MHE type among the alternatives for each material flow link is searched. Knowledge-based rules are employed to retrieve the alternatives for each material flow link. To consider and compare the alternatives, multiple design factors are considered. These factors include both quantitative and qualitative measures. The qualitative measures are converted to numerical measures using fuzzy logic. The concept of fuzzy logic is applied to evaluation matrices used for the selection of the most suitable MHE through a fuzzy linguistic approach. Thus, this paper demonstrates the potential applicability of fuzzy theory in the MHE applications and provides a systemic guidance in the decision-making process.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.3-8
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• 1998

The present work proposes the potential fuzzy framework, based on fuzzy set theory, for supporting decision-making problems, especially, selection problems of a best design in the area of nuclear energy system. The framework proposed is composed of the hierarchical structure module, the assignment module, the fuzzification module, and the defuzzification module. In the structure module, the relationship among decision objectives, decision criteria, decision sub-criteria, and decision alternatives is hierarchically structured. In the assignment module, linguistic or rank scoring approach can be used to assign subjective and/or vague values to the decision analyst's judgment on decision variables. In the fuzzification module, fuzzy numbers are assigned to these values of decision variables. Using fuzzy arithmetic operations, for each alternative, fuzzy preference index as a fuzzy synthesis measure is obtained. In the defuzzification module, using one of methods ranking fuzzy numbers, these indices are defuzzified to overall utility values as a cardinality measure determining final scores. According these values, alternatives of interest are ranked and an optimal alternative is chosen. To illustrate the applicability of the framework proposed to selection problem, as a case example, the best option choice of four design options under five decision criteria for primary containment wall thickening around large penetrations in an advanced nuclear energy system is studied.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.21-29
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• 1996

It is very important to select the best alternative for a manufacturing enterprise. However, more often than not this work is carried out unsatisfactorily. In this paper, we will present a new model for evaluating alternatives. Two main results derived from this paper are as follows: 1. A selection model of alternative is suggested that each decision maker's opinion is equally evaluated and the preference of each attribute can also be considered simultaneously. 2. A proposed method is especially effective to analyze a data structure with fuzzy and crisp data.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.181-184
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• 1996

Fuzzy hierarchical analysis(FHA) has the usefulness to allow decision maker's ambiguities when comparing two alternatives. But, for easiuly appling it to a decision problem, the handling its many data and for decision makers much not knowing fuzzy theory are the obstacles to must be overcomed even if the results of final fuzzy weights can be computed by a personal computer. This paper decribes that FHA is revised, and input/output interfaces are developed to collect input data easily and interprete the fuzzy resultlts. Finally, a fuzzy decision process is suggested with them.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.89-95
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• 2007

In general, reliability of AHP(Analytic Hierarchy Process) depends on pairwise comparison of evaluators. In addition, human judgment on the importance of alternatives or criteria is always imprecise and vague. To cope with these shortcomings, Fuzzy AHP is suggested and used widely recently. But in Fuzzy AHP, it cannot deal with the evaluator's various attitudes towards risk and confidence owing to evaluator's different expertise and experience. This paper proposes a method for consideration of evaluator's confidence and risk attitude in Fuzzy AHP. And suggested methods are applied various scenarios to verify the meaningfulness. The result shows that the priority of alternatives can be change through the consideration of evaluator's confidence and risk attitude.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.917-920
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• 1993

Various forms of hardware alternatives exist for the implementation of fuzzy logic controllers. In this paper, we describe a systematic framework for realizing fuzzy heuristics on programmable-logic-devices. Our approach is suitable for the automated development of fuzzy logic controllers.